I never really understood the argument that OpenAI has some technology that Google does not have. That's just not true. The opposite is much more true. And Google's LaMDA is even older than ChatGPT.
Google has to be a long way off monetizing what they have though. If Google was in a position to roll out AI soon I can't imagine why they'd be getting rid of 12,000 people who they know can pass their hiring criteria. They would put some of those engineers to work integrating the AI code into Google's products. Unless Google's AI is so good it can integrate itself I suppose.
The fact they're letting 12,000 people go shows they don't have profitable work for those people. That alone should tell us something about the position of Google's AI strategy right now.
Do we actually know a bit more on what people were let go, from what teams? Maybe the percentage of AI people in Google actually has grown relatively now?
And Google is in fact using AI almost everywhere in production already. You have some sort of AI in almost every product. Also language models are everywhere, e.g. just prediction of typing on your phone, or in GMail, in speech recognition, and many other places. I think they just do not use the biggest models for those things but some more efficient models, which can partly even run offline on your device (e.g. for the typing prediction).
Also in Google search, they use lots of AI, also neural networks.
It's just that for LaMDA specifically, they don't have a good product yet.
> The formula looks at the variables below, and then spits out a "number" for every Googler. Each PA VP gets a % to cut, and as such there is a threshold. Anyone below that threshold gets RIF'd.
Variables are:
1) Location of labor. US Premium Plus was largely impacted versus cheaper areas.
2) Tenure and performance in level.
3) "Runway" of comp. (e.g. base salary vs MRP. eg. .8 of MRP Googlers have a long runway, vs 1.x of MRP Googlers are basically top of band, and 'tenured' with no runway except promo
4) Promo velocity
Anyways, I didn't understand the acronyms so I decided to feed it to GPT and it definitely made it easier to understand:
Google is using a formula to determine which employees will be laid off (known as RIF: Reduction in Force)
The formula takes into account various factors such as location of labor (with US Premium Plus areas being more heavily impacted), tenure and performance in the current level, "runway" of compensation (the difference between base salary and maximum potential salary), and promo velocity (how quickly the employee has been promoted within the company)
This formula calculates a "number" for each employee based on these factors
Each Product Area Vice President (PA VP) is given a percentage of employees they must lay off
Employees with a score below a certain threshold, determined by the formula, will be laid off
> That alone should tell us something about the position of Google's AI strategy right now.
Not really? Maybe they believe those 12000 people have the wrong skills for this job. Maybe they believe they can get the AI integrated with a lot less people. Maybe they would have fired 20k people, but decided to keep 8k of those to integrate the language generative model into products.
Not saying any of this is true. In fact more likely that the company is just reacting randomly without a big overarching plan. I'm just saying that I don't think you can draw conclusions from the fact that layoffs are happening about their AI strategy.
Google has to be a long way off monetizing what they have though. If Google was in a position to roll out AI soon I can't imagine why they'd be getting rid of 12,000 people who they know can pass their hiring criteria. They would put some of those engineers to work integrating the AI code into Google's products. Unless Google's AI is so good it can integrate itself I suppose.
The fact they're letting 12,000 people go shows they don't have profitable work for those people. That alone should tell us something about the position of Google's AI strategy right now.